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Data mining techniques for enhancing stock allocation managementData mining techniques for enhancing stock allocation management description/claimsThe Patent Description & Claims data below is from USPTO Patent Application 20070255636, Data mining techniques for enhancing stock allocation management. Brief Patent Description - Full Patent Description - Patent Application Claims
BACKGROUND OF THE INVENTION [0001] 1. Field of the Invention [0002] This invention relates to methodology for utilizing data mining techniques in the area of stock allocation management. [0003] 2. Introduction to the Invention [0004] Data mining techniques are known and include disparate technologies, like neural networks, which can work to an end of efficiently discovering valuable, non-obvious information from a large collection of data. The data, in turn, may arise in fields ranging from e.g., marketing, finance, manufacturing, or retail. SUMMARY OF THE INVENTION [0005] We have now discovered novel methodology for exploiting the advantages inherent generally in data mining technologies, in the particular field of stock allocation management applications. [0006] Our work proceeds in the following way. [0007] We have recognized that a typical and important "three-part" paradigm for presently effecting stock allocation management, is a largely subjective, human paradigm, and therefore exposed to all the vagaries and deficiencies otherwise attendant on human procedures. In particular, the three-part paradigm we have in mind works in the following way. First, a stock allocation manager develops a demand database comprising a compendium of individual demand history--e.g., the demand's response to historical supply situations. Secondly, and independently, the stock allocation manager develops in his mind a supply database comprising the stock allocation manager's personal, partial, and subjective knowledge of objective retail facts culled from e.g., the marketing literature, the business literature, or input from colleagues or salespersons. Thirdly, the stock allocation manager subjectively correlates in his mind the necessarily incomplete and partial supply database, with the demand database, in order to promulgate an individual's demand's prescribed stock allocation management evaluation and cure. [0008] This three-part paradigm is part science and part art, and captures one aspect of the problems associated with stock allocation management. However, as suggested above, it is manifestly a subjective paradigm, and therefore open to human vagaries. [0009] We now disclose a novel computer method which can preserve the advantages inherent in this three-part paradigm, while minimizing the incompleteness and attendant subjectivities that otherwise inure in a technique heretofore entirely reserved for human realization. [0010] To this end, in a first aspect of the present invention, we disclose a novel computer method comprising the steps of: [0011] i) providing a demand database comprising a compendium of demand retail history; [0012] ii) providing a supply database comprising a compendium of at least one of stock allocation management solutions, stock allocation information, and stock allocation diagnostics; and [0013] iii) employing a data mining technique for interrogating said demand and supply databases for generating an output data stream, said output data stream correlating demand problem with supply solution. [0014] The novel method preferably comprises a further step of updating the step i) demand database, so that it can cumulatively track the demand history as it develops over time. For example, this step i) of updating the demand database may include the results of employing the step iii) data mining technique. Also, the method may comprise a step of refining an employed data mining technique in cognizance of pattern changes embedded in each database as a consequence of supply results and updating the demand database. [0015] The novel method preferably comprises a further step of updating the step ii) supply database, so that it can cumulatively track an ever increasing and developing technical stock allocation management literature. For example, this step ii) of updating the supply database may include the effects of employing a data mining technique on the demand database. Also, the method may comprise a step of refining an employed data mining technique in cognizance of pattern changes embedded in each database as a consequence of supply results and updating the supply database. [0016] The novel method may employ advantageously a wide array of step iii) data mining techniques for interrogating the demand and supply database for generating an output data stream, which output data stream correlates demand problem with supply solution. For example, the data mining technique may comprise inter alia employment of the following functions for producing output data: classification-neural, classification-tree, clustering-geographic, clustering-neural, factor analysis, or principal component analysis, or expert systems. [0017] In a second aspect of the present invention, we disclose a program storage device readable by machine to perform method steps for providing an interactive stock allocation management database, the method comprising the steps of: [0018] i) providing a demand database comprising a compendium of individual demand history; [0019] ii) providing a supply database comprising a compendium of at least one of stock allocation management solutions, stock allocation information, and stock allocation diagnostics; and [0020] iii) employing a data mining technique for interrogating said demand and supply databases for generating an output data stream, said output data stream correlating demand problem with supply solution. [0021] In a third aspect of the present invention, we disclose a computer comprising: [0022] i) means for inputting a demand database comprising a compendium of individual demand history; [0023] ii) means for inputting a supply database comprising a compendium of at least one of stock allocation management solutions, stock allocation information, and stock allocation diagnostics; [0024] iii) means for employing a data mining technique for interrogating said supply databases; and [0025] iv) means for generating an output data stream, said output data stream correlating demand problem with supply solution. BRIEF DESCRIPTION OF THE DRAWING [0026] The invention is illustrated in the accompanying drawing, in which [0027] FIG. 1 provides an illustrative flowchart comprehending overall realization of the method of the present invention; [0028] FIG. 2 provides an illustrative flowchart of details comprehended in the FIG. 1 flowchart; [0029] FIG. 3 shows a neural network that may be used in realization of the FIGS. 1 and 2 data mining algorithm; and [0030] FIG. 4 shows further illustrative refinements of the FIG. 3 neural network. DETAILED DESCRIPTION OF THE PRESENT INVENTION Continue reading about Data mining techniques for enhancing stock allocation management... 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